Does this skill require any external tools?

Yes, you must have yt-dlp installed on your system via pip or Homebrew for the skill to successfully extract transcripts from YouTube URLs.

Can it handle videos without captions?

If a video lacks both auto-generated and manual captions, the skill will inform you and offer alternative approaches, such as analyzing the video description or comments.

Will it save files to my project directory?

No, the skill is designed to create and use a temporary directory for all downloaded transcripts and metadata to keep your repository clutter-free.

How does it handle very long videos?

For videos over 45 minutes, the skill utilizes intelligent chunking to process the transcript in logical segments, maintaining context while staying within token limits.

Can it analyze videos in languages other than English?

The skill prefers English transcripts by default but can be configured to check for and list other available subtitle languages if an English version is unavailable.

YouTube Transcript Analyzer

Name: YouTube Transcript Analyzer
Author: Light-Brands

byLight-Brands

Aprendizaje y Documentación

Extracts and analyzes YouTube video transcripts to provide actionable insights, technical summaries, and project-specific recommendations.

Acerca de

This skill streamlines the process of learning from video content by automatically downloading, chunking, and analyzing YouTube transcripts using yt-dlp. It goes beyond simple summarization by relating video concepts directly to your current codebase, highlighting technical patterns, and providing specific recommendations with timestamp references. Whether you are researching a new library through a tutorial or extracting key takeaways from a conference talk, this skill helps you digest long-form video content efficiently without needing to watch the entire video.

Características Principales

Metadata extraction to provide author and video context during analysis
Precise timestamp referencing for key concepts and technical demonstrations
Automated transcript extraction using yt-dlp with support for auto-generated captions
0 GitHub stars
Context-aware analysis that compares video content with your current codebase
Intelligent chunking and synthesis for long-form content exceeding 45 minutes

Casos de Uso

Researching complex technical concepts from conference talks or software tutorials
Comparing external video-based methodologies with your existing project architecture
Extracting code patterns and implementation details from developer demonstrations

Acerca de

Características Principales

Metadata extraction to provide author and video context during analysis
Precise timestamp referencing for key concepts and technical demonstrations
Automated transcript extraction using yt-dlp with support for auto-generated captions
0 GitHub stars
Context-aware analysis that compares video content with your current codebase
Intelligent chunking and synthesis for long-form content exceeding 45 minutes

Casos de Uso

Researching complex technical concepts from conference talks or software tutorials
Comparing external video-based methodologies with your existing project architecture
Extracting code patterns and implementation details from developer demonstrations